Cardiology is the speciality with the second largest grouping of U.S. Food and Drug Administration (FDA) cleared artificial intelligence (AI) applications, trailing only radiology. A sizeable number of these cardiology-focused AI algorithms are for cardiac ultrasound, and that number is growing.

Researchers out of Rutgers University in New Jersey have used artificial intelligence (AI) to anticipate when patients may present with atrial fibrillation (AFib), heart failure and other cardiovascular conditions, sharing their findings in Genomics.

Google’s medically focused generative artificial intelligence model achieved 85% accuracy on a U.S. Medical Licensing Examination (USMLE) practice test, the highest score ever recorded by an AI model, according to preliminary results shared by the Google Health AI team.

DiA Imaging Analysis, an Israel-based healthcare technology company, has gained U.S. Food and Drug Administration (FDA) clearance for LVivo IQS, a new software solution designed to help users acquire high-quality echocardiography images, regardless of their experience.

The vast majority of 500 artificial intelligence (AI) algorithms now cleared for clinical use in the U.S. are for radiology and cardiology. For this reason, cardiologists and radiologists need to learn how these technologies work and realise the clinical use of AI is no longer science fiction.

The integration of artificial intelligence into radiology PACS and enterprise imaging systems has become a big topic of discussion with IT vendors over the past couple years. This has become a bigger question from hospitals and radiology groups as there are now about 400 radiology related AI algorithms that have U.S. Food and Drug Administration...

Text-generating AI models, such as ChatGPT, have the potential to “revolutionise the field of medical writing” by automating tasks and increasing efficiency throughout the writing process.

An AI tool named “Sybil” was able to forecast both short- and long-term lung cancer risk based on a single low-dose CT (LDCT) scan, researchers reported.

In efforts to speed workflow, improve patient care and augment an increasingly shorthanded clinical workforce, AI is starting to see wider adoption across healthcare. But there are questions regarding who is liable if an AI application fails and it results in a malpractice lawsuit.

Two artificial intelligence (AI) programs, including ChatGPT, have passed the U.S. Medical Licensing Examination (USMLE), according to two recent papers.